scholarly journals Novel Route Planning System for Machinery Selection. Case: Slurry Application

2020 ◽  
Vol 2 (3) ◽  
pp. 408-429 ◽  
Author(s):  
Mahdi Vahdanjoo ◽  
Christian Toft Madsen ◽  
Claus Grøn Sørensen
Keyword(s):  
Vehicle Routing Problem ◽  
Route Planning ◽  
Optimal Solution ◽  
Application Rate ◽  
Planning System ◽  
Application Process ◽  
Optimal Sequence ◽  
Routing Problem ◽  
Optimization And Simulation ◽  
Working Distance

The problem of finding an optimal solution for the slurry application process is casted as a capacitated vehicle routing problem (CVRP) in which by considering the vehicle’s capacity, it is required to visit all the tracks only once to fully cover the field, as well as complying with a specified targeted application rate. A key objective in this study was to determine an optimized coverage plan in order to minimize the driving distance in the field, while at the same time allowing for varying the application rate. The coverage plan includes the optimal sequence of tracks with a specified application rate for each track. Two algorithms were developed for optimization and simulation of the slurry application cast as capacitated operations. In order to validate the proposed algorithms, a slurry application operation was recorded, and the results of the optimization algorithm were compared with the conventional non-optimized method. The comparison showed that applying the proposed new method reduces the non-working distance by 18.6% and the non-working time by 28.1%.

scholarly journals Novel Route Planning Method to Improve the Operational Efficiency of Capacitated Operations. Case: Application of Organic Fertilizer

2021 ◽  
Vol 3 (3) ◽  
pp. 458-477
Author(s):  
Mahdi Vahdanjoo ◽  
Claus G. Sorensen
Keyword(s):  
Organic Fertilizer ◽  
Route Planning ◽  
Fertilizer Application ◽  
Operational Efficiency ◽  
Application Rate ◽  
Simultaneous Optimization ◽  
Limiting Factor ◽  
Application Process ◽  
Optimal Sequence ◽  
Proposed Model

A field area coverage-planning algorithm has been developed for the optimization and simulation of capacitated field operations such as the organic fertilizer application process. The proposed model provides an optimal coverage plan, which includes the optimal sequence of the visited tracks with a designated application rate. The objective of this paper is to present a novel approach for route planning involving two simultaneous optimization criteria, non-working distance minimization and the optimization of application rates, for the capacitated field operations such as organic fertilizer application to improve the overall operational efficiency. The study and the developed algorithm have shown that it is possible to generate the optimized coverage plan based on the required defined capacity of the distributer. In this case, the capacity of the distributer is not considered a limiting factor for the farmers. To validate this new method, a shallow injection application process was considered, and the results of applying the optimization algorithm were compared with the conventional methods. The results show that the proposed method increase operational efficiency by 19.7%. Furthermore, the applicability of the proposed model in robotic application were demonstrated by way of two defined scenarios.

scholarly journals Capacitated vehicle routing problem model for carriers

2018 ◽  
Vol 12 ◽  
Author(s):  
Irma-Delia Rojas-Cuevas ◽  
Santiago-Omar Caballero-Morales ◽  
Jose-Luis Martinez-Flores ◽  
Jose-Rafael Mendoza-Vazquez
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Network Flow ◽  
Route Planning ◽  
Test Problems ◽  
Optimal Route ◽  
Routing Problem ◽  
Problem Model ◽  
Capacitated Vehicle Routing Problem ◽  
Capacitated Vehicle

Background: The Capacitated Vehicle Routing Problem (CVRP) is one of the most important transportation problems in logistics and supply chain management. The standard CVRP considers a fleet of vehicles with homogeneous capacity that depart from a warehouse, collect products from (or deliver products to) a set of customer locations (points) and return to the same warehouse. However, the operation of carrier companies and third-party transportation providers may follow a different network flow for collection and delivery. This may lead to non-optimal route planning through the use of the standard CVRP.Objective: To propose a model for carrier companies to obtain optimal route planning.Method: A Capacitated Vehicle Routing Problem for Carriers (CVRPfC) model is used to consider the distribution scenario where a fleet of vehicles depart from a vehicle storage depot, collect products from a set of customer points and deliver them to a specific warehouse before returning to the vehicle storage depot. Validation of the model’s functionality was performed with adapted CVRP test problems from the Vehicle Routing Problem LIBrary. Following this, an assessment of the model’s economic impact was performed and validated with data from a real carrier (real instance) with the previously described distribution scenario.Results: The route planning obtained through the CVRPfC model accurately described the network flow of the real instance and significantly reduced its distribution costs.Conclusion: The CVRPfC model can thus improve the competitiveness of the carriers by providing better fares to their customers, reducing their distribution costs in the process.

Solving vehicle routing problem by using improved genetic algorithm for optimal solution

2017 ◽  
Vol 21 ◽  
pp. 255-262 ◽  
Author(s):  
Mazin Abed Mohammed ◽  
Mohd Khanapi Abd Ghani ◽  
Raed Ibraheem Hamed ◽  
Salama A. Mostafa ◽  
Mohd Sharifuddin Ahmad ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Optimal Solution ◽  
Improved Genetic Algorithm ◽  
Routing Problem

Meta-heuristic Approach to Solve Mixed Vehicle Routing Problem with Backhauls in Enterprise Information System of Service Industry

2010 ◽  
pp. 210-225
Author(s):  
S. P. Anbuudayasankar ◽  
K. Ganesh ◽  
Tzong-Ru Lee
Keyword(s):  
Vehicle Routing ◽  
Enterprise Resource Planning ◽  
Vehicle Routing Problem ◽  
Service Industry ◽  
Optimal Solution ◽  
Resource Planning ◽  
Enterprise Information ◽  
Solution Quality ◽  
Routing Problem ◽  
Support Tool

This chapter presents the development of simulated annealing (SA) for a health care application which is modeled as Single Depot Vehicle routing problem called Mixed Vehicle Routing Problem with Backhauls (MVRPB), an extension of Vehicle Routing Problem with Backhauls (VRPB). This variant involves both delivery and pick-up customers and sequence of visiting the customers is mixed. The entire pick-up load should be taken back to depot. The latest rapid advancement of meta-heuristics has shown that it can be applied in practice if they are personified in packaged information technology (IT) solutions along with the combination of a Supply Chain Management (SCM) application integrated with an enterprise resource planning (ERP) resulted to this decision support tool. This chapter provides empirical proof in sustain of the hypothesis, that a population extension of SA with supportive transitions leads to a major increase of efficiency and solution quality for MVRPB if and only if the globally optimal solution is located close to the center of all local optimal solutions.

scholarly journals A Heuristic Solution Method for Multi-Depot Vehicle Routing-Based Waste Collection Problems

2020 ◽  
Vol 10 (7) ◽  
pp. 2403
Author(s):  
Yanjun Shi ◽  
Lingling Lv ◽  
Fanyi Hu ◽  
Qiaomei Han
Keyword(s):  
Vehicle Routing ◽  
Waste Disposal ◽  
Vehicle Routing Problem ◽  
Solution Method ◽  
Search Algorithm ◽  
Optimal Solution ◽  
Waste Collection ◽  
Heuristic Solution ◽  
Routing Problem ◽  
Combination Optimization

This paper addresses waste collection problems in which urban household and solid waste are brought from waste collection points to waste disposal plants. The collection of waste from the collection points herein is modeled as a multi-depot vehicle routing problem (MDVRP), aiming at minimizing the total transportation distance. In this study, we propose a heuristic solution method to address this problem. In this method, we firstly assign waste collection points to waste disposal plants according to the nearest distance, then each plant solves the single-vehicle routing problem (VRP) respectively, assigning customers to vehicles and planning the order in which customers are visited by vehicles. In the latter step, we propose the sector combination optimization (SCO) algorithm to generate multiple initial solutions, and then these initial solutions are improved using the merge-head and drop-tail (MHDT) strategy. After a certain number of iterations, the optimal solution in the last generation is reported. Computational experiments on benchmark instances showed that the initial solutions obtained by the sector combination optimization algorithm were more abundant and better than other iterative algorithms using only one solution for initialization, and the solutions with distance gap were obtained using the merge-head and drop-tail strategy in a lower CPU time compared to the Tabu search algorithm.

Practical aspects of the split delivery vehicle routing problem (SDVRP)

2018 ◽  
Vol 120 ◽  
pp. 155-166
Author(s):  
Marek Karkula
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Route Planning ◽  
Product Distribution ◽  
Delivery Vehicle ◽  
Routing Problem ◽  
Split Delivery ◽  
Delivery Planning ◽  
Distribution Company ◽  
Planning Problems

Transport process arrangement and delivery route planning is one of the most important tasks of managers in distribution, trade and production enterprises. The problem of route planning concerns the rationalization of product distribution processes offered by company for the customer's network. In operational research, such a problem is included in the class of issues of Vehicle Routing Problem – VRP. The VRP delivery planning problems constitute a wide family of issues arising primarily from the conditions and constraints of the practice. The paper presents the practical application of one of the VRP variants – the problem of arranging routes for the Split Delivery Vehicle Routing Problem – SDVRP, and the results of analyses based on research carried out in a distribution company.

scholarly journals A Dynamic Route-Planning System Based on Industry 4.0 Technology

Algorithms ◽  
2020 ◽  
Vol 13 (12) ◽  
pp. 308
Author(s):  
Duy Nguyen Duc ◽  
Thong Tran Huu ◽  
Narameth Nananukul
Keyword(s):  
Machine Learning ◽  
Real Time ◽  
Industry 4.0 ◽  
Big Data Analytics ◽  
Route Planning ◽  
Research Area ◽  
Automated Guided Vehicles ◽  
Planning System ◽  
Routing Problem ◽  
Dynamic Route

Due to the availability of Industry 4.0 technology, the application of big data analytics to automated systems is possible. The distribution of products between warehouses or within a warehouse is an area that can benefit from automation based on Industry 4.0 technology. In this paper, the focus was on developing a dynamic route-planning system for automated guided vehicles within a warehouse. A dynamic routing problem with real-time obstacles was considered in this research. A key problem in this research area is the lack of a real-time route-planning algorithm that is suitable for the implementation on automated guided vehicles with limited computing resources. An optimization model, as well as machine learning methodologies for determining an operational route for the problem, is proposed. An internal layout of the warehouse of a large consumer product distributor was used to test the performance of the methodologies. A simulation environment based on Gazebo was developed and used for testing the implementation of the route-planning system. Computational results show that the proposed machine learning methodologies were able to generate routes with testing accuracy of up to 98% for a practical internal layout of a warehouse with 18 storage racks and 67 path segments. Managerial insights into how the machine learning configuration affects the prediction accuracy are also provided.

A Survey of Autonomous Control Algorithms by Means of Adapted Vehicle Routing Problems

2008 ◽  
Author(s):  
Bernd Scholz-Reiter ◽  
Henning Rekersbrink ◽  
Bernd-Ludwig Wenning ◽  
Thomas Makuschewitz
Keyword(s):  
Vehicle Routing ◽  
Routing Protocol ◽  
Vehicle Routing Problem ◽  
Paradigm Shift ◽  
Collaborative Research ◽  
Optimal Solution ◽  
Routing Algorithms ◽  
Research Centre ◽  
Control Algorithms ◽  
Routing Problem

The German Collaborative Research Centre 637 “Autonomous Cooperating Logistic Processes – A Paradigm Shift and its Limitations”, develops, among other things, autonomous routing algorithms for transport networks. The discussed algorithm is designed to match goods and vehicles and to continuously make route decisions within a dynamic transport network. Here, each object makes its own decisions. It is called Distributed Logistics Routing Protocol – DLRP. Because of obvious similarities to the Vehicle Routing Problem (VRP), one question arises for both practitioners and researchers: How efficient is this protocol compared to traditional, established algorithms or in comparison to the optimal solution? This article tries to answer this question, which appears simple on the first and challenging on the second view.

A Improved Pareto of Ant Colony Algorithm to Solve the Vehicle Routing Problem with Time Windows

2014 ◽  
Vol 1030-1032 ◽  
pp. 1941-1944
Author(s):  
Hong Dou Zhang ◽  
Ning Guo ◽  
Jian Lin Mao ◽  
Hai Feng Wang
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Ant Colony Algorithm ◽  
Transition Probability ◽  
Time Windows ◽  
Optimal Solution ◽  
Ant Colony ◽  
Local Optimum ◽  
Routing Problem ◽  
Important Extension

Vehicle routing problem with time Windows (VRPTW) that is a kind of important extension type for VPR. In view of problem which the ant colony algorithm in solving VRPTW easily plunged into local optimum , this paper defines a new ant transition probability of saving ideas, and uses the Pareto optimal solution set of global pheromone updating rule, and puts forward a kind of improved Pareto ant colony algorithm (IPACA) . Through the simulation experiments show that IPACA improves the global search ability of ACA, effectively avoids the algorithm falls into local optimum, and reduces the total distribution cost (distance), so as to verify the effectiveness of the proposed algorithm.

An Improved Ant Colony Optimization for VRP with Time Windows

2012 ◽  
Vol 263-266 ◽  
pp. 1609-1613 ◽  
Author(s):  
Su Ping Yu ◽  
Ya Ping Li
Keyword(s):  
Ant Colony Optimization ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Distribution Systems ◽  
Optimization Problems ◽  
Time Windows ◽  
Optimal Solution ◽  
Ant Colony ◽  
Routing Problem ◽  
Combinatorial Optimization Problems

The Vehicle Routing Problem (VRP) is an important problem occurring in many distribution systems, which is also defined as a family of different versions such as the Capacitated Vehicle Routing Problem (CVRP) and the Vehicle Routing Problem with Time Windows (VRPTW). The Ant Colony Optimization (ACO) is a metaheuristic for combinatorial optimization problems. Given the ACO inadequacy, the vehicle routing optimization model is improved and the transfer of the algorithm in corresponding rules and the trajectory updated regulations is reset in this paper, which is called the Improved Ant Colony Optimization (I-ACO). Compared to the calculated results with genetic algorithm (GA) and particle swarm optimization (PSO), the correctness of the model and algorithm is verified. Experimental results show that the I-ACO can quickly and effectively obtain the optimal solution of VRFTW.

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